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Close2U: An App for Monitoring Cancer Patients with Enriched Information from Interaction Patterns.

Javier Navarro-Alamán1, Raquel Lacuesta1,2, Iván García-Magariño3,4

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This study introduces an application for systematic cancer patient symptom data collection and visualization. Analyzing patient data alongside interaction patterns enhances understanding of their condition and improves clinical care.

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Area of Science:

  • Oncology
  • Health Informatics
  • Human-Computer Interaction

Background:

  • Effective management of cancer patient symptoms is crucial for clinical care and monitoring disease progression.
  • Systematic data collection and visualization are essential for tracking patient evolution.

Purpose of the Study:

  • To present an application for periodic and systematic collection and visualization of cancer patient data.
  • To analyze the correlation between collected patient data and interaction patterns to enrich user information.
  • To evaluate the application's effectiveness in supporting clinical decision-making.

Main Methods:

  • Agile methodology with iterative and incremental development of prototypes.
  • Systematic data collection of cancer patient symptoms (mood, sleep, pain).
  • Analysis of correlations between patient data and user interaction patterns.

Main Results:

  • Demonstrated the feasibility of systematically collecting and visualizing cancer patient symptom data.
  • Identified correlations between patient states (mood, sleep, pain) and interaction patterns.
  • Established a foundation for enriching patient information through interaction analysis.

Conclusions:

  • The developed application supports enhanced monitoring of cancer patient symptoms.
  • Integrating interaction patterns with patient data offers potential for deeper clinical insights.
  • Future work aims to optimize data collection, analysis, and reporting efficiency.